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Princeton University mathematician York Dobyns found that the seven years of new PEAR RNG results closely replicated the preceding three decades of RNG studies reviewed in the meta-analysis.37 That is, our 1989 prediction had been validated. Because the massive PEAR database provides an exceptionally strong confirmation that mind-matter interactions really do exist, we can confidently use it to study some of the factors influencing these effects. Psychologist Roger Nelson and his colleagues found that the main RNG effect for the full PEAR database of 1,262 independent experiments, generated by 108 people, was associated with odds against chance of four thou sand to one.38 He also found that there were no “star” performers—this means that the overall effect reflected an accumulation of small effects from each person rather than a few outstanding results from “special people.” This finding confirms the expectation that mind-matter interaction effects observed in the hundreds of studies collected in the 1989 RNG meta-analysis were part of a widespread ability distributed throughout the population, and were not due to a few psychic “superstars” or a few odd experiments. Further analysis of the PEAR data showed that the results in individual trials were best interpreted as small changes in the probabilities of individual random events rather than as a few instances of wildly large effects. This means that the results cannot be explained by unexpected glitches in the RNG devices, or by strange circumstances in the lab (like a circuit breakdown). Rather, the effects were small but consistent across individual trials, and across different people.39 If we accept that one person can affect the behavior of an RNG, another question naturally arises: would two people together produce a larger effect? The PEAR database included some experiments where cooperating pairs used the same mental intention on the same RNG. Analysis of these data found that, on average, the effects were indeed larger for pairs than for individuals working alone. However, two people didn’t automatically get results that were twice as large as one person’s results. Instead, the composition of the pairs was important in determining the outcome. Same-sex pairs, whether men or women, tended to achieve null or slightly negative outcomes, whereas opposite-sex pairs produced an effect that was approximately twice that of individuals. Moreover, when the pair was a “bonded” couple, such as spouses or close family members, the effect size was more than four times that of individuals. There were also some gender differences. PEAR lab psychologist Brenda Dunne found that women tended to volunteer more time to the experiments, and thus they accumulated about two-thirds of the full database, compared with one-third for men. On the other hand, their effects were smaller on average than those of men, with odds of the difference being due to chance at eight hundred to one.
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